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Modeling with Rules Using Semantic Knowledge Engineering pp 27–48Cite as

Knowledge Engineering with Rules

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 130))

Abstract

Intelligent systems that use knowledge representation and reasoning methods are commonly referred to as knowledge-based systems. The domain that considers building them is most generally referred to as knowledge engineering. This chapter introduces some of the important knowledge engineering topics with respect to rule-based systems. We discuss the modeling of acquired knowledge with the use of rules and other representations supporting the design. Once a rule set is built, an inference mechanism should be considered. In the case of large rule sets their structure has to be considered. The quality of the rule base should be analyzed during the design, or at least after it. If possible, the rule base should be kept independent of the specific system implementation. To make this possible a specific rule interchange method can be used. Finally, as today rule-based systems are not usually stand-alone systems, specific architectures for their integration are discussed.

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Notes

  1. 1.

    The rented car category corresponds to Euro Car Segment classification, see: http://en.wikipedia.org/wiki/Euro_Car_Segment.

  2. 2.

    Furthermore, they are useful to be integrated with user dialogs.

  3. 3.

    Lukichev shows that RIF does not specify guidelines regarding how to implement a transformation from a source rule language into the RIF and, what is more, how to verify the correctness of already made translations [66]. In turn, in [67] Wang et al. indicate that, from the perspective of modeling, RIF does not have meta-model to describe features of rules.

  4. 4.

    See: http://wiki.ruleml.org.

  5. 5.

    See: http://oxygen.informatik.tu-cottbus.de/rewerse-i1/.

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    Grzegorz J. Nalepa

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Nalepa, G.J. (2018). Knowledge Engineering with Rules. In: Modeling with Rules Using Semantic Knowledge Engineering. Intelligent Systems Reference Library, vol 130. Springer, Cham. https://doi.org/10.1007/978-3-319-66655-6_2

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